Regularity and Genetic Relatedness in Signed Language

对手语的科学研究为人类的语言能力以及口语和手语模式之间的差异提供了见解。研究表明，所有的人类语言都随着时间的推移而变化，无论形式如何。有大量关于口语变化的概括，这些概括通常与人类语言相关。然而，绝大多数人类语言变化的一般特征都是在没有考虑手语的情况下开发的。在口语中，联合收割机组成单词的声音经常随着时间的推移以规则和系统的方式变化，这些规则的声音变化形成了语言家族的经验基础。符号语言有联合收割机组成符号的单位，但没有研究表明有规律的语音变化在符号语言中是否有相关性，或者有规律的语言变化是否是口语所特有的。这个项目将是第一个严格探索这个问题的项目。它还将为几名本科生提供研究经验，并为一名博士后提供专业发展。这个为期三年的项目将调查13种手语之间的语言变化和关系。它将利用在线和印刷词典，为每种语言的207个基本概念开发一个符号数据库。语言的聋人本地签名者将检查签名并提供缺失的条目。每个符号都将被转录，以便在所有语言中手动和自动比较符号的语音单位。然后将使用两种方法对数据集进行评估：传统的比较方法（CM）和基于网络的贝叶斯系统发育方法。如果CM产生了规则和重复对应的证据，研究人员将识别同源词并重建语言的早期阶段。缺乏这种对应性将提供证据表明，签名语言的某些方面抑制或掩盖了CM所依赖的规则变化。定量系统发育方法是对CM的补充，因为它们不依赖于定期变化来评估语言之间的相似性模式。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

The scientific study of signed languages has provided insights into the human capacity for language and differences between spoken and signed modalities. Studies reveal that all human languages change over time—regardless of modality. There is a large body of generalizations about spoken language change, which are typically framed as relevant for human language generally. However, the vast majority of the proposed general features of human language change were developed without consideration of signed languages. In spoken language, the sounds that combine to form words often change in regular and systematic ways over time, and these regular sound changes form the empirical basis for language families. Signed languages have units that combine to form signs, but no research has been done to clarify whether regular sound change has a correlate in signed languages, or if regular language change is unique to spoken languages. This project will be the first to rigorously explore this question. It will also provide research experience to several undergraduates and professional development to a postdoctoral associate.The three-year project will investigate linguistic change and relationships among 13 signed languages. It will develop a database of signs for 207 basic concepts in each language, drawing on online and print dictionaries. Deaf native signers of the languages will check the signs and provide missing entries. Each sign will be transcribed to allow both manual and automated comparisons of the signs’ phonological units across all languages. The dataset will then be evaluated using two methodologies: the traditional Comparative Method (CM), and network-based and Bayesian phylogenetic approaches. If the CM yields evidence of regular and recurring correspondences, the researchers will identify cognates and reconstruct earlier stages of the languages. Lack of such correspondences will provide evidence that some aspect of signed languages either inhibits or disguises the regular changes on which the CM depends. Quantitative phylogenetic approaches are complementary to the CM because they do not depend on regular change to assess patterns of similarity among languages.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.